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Sequential Diagnosis in the Independence Bayesian Framework

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Soft-Ware 2002: Computing in an Imperfect World (Soft-Ware 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2311))

Abstract

We present a new approach to test selection in sequential diagnosis (or classification) in the independence Bayesian framework that resembles the hypothetico-deductive approach to test selection used by doctors. In spite of its relative simplicity in comparison with previous models of hypotheticodeductive reasoning, the approach retains the advantage that the relevance of a selected test can be explained in strategic terms. We also examine possible approaches to the problem of deciding when there is sufficient evidence to discontinue testing, and thus avoid the risks and costs associated with unnecessary tests.

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Author information

Authors and Affiliations

  1. School of Information and Software Engineering, University of Ulster, BT52 1SA, Coleraine, Northern Ireland

    David McSherry

Authors
  1. David McSherry
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Editor information

Editors and Affiliations

  1. Faculty of Informatics School of Information and Software Engineering, University of Ulster, Jordanstown Campus, BT37 0QB, Newtownabbey, Northern Ireland

    David Bustard , Weiru Liu  & Roy Sterritt ,  & 

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© 2002 Springer-Verlag Berlin Heidelberg

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McSherry, D. (2002). Sequential Diagnosis in the Independence Bayesian Framework. In: Bustard, D., Liu, W., Sterritt, R. (eds) Soft-Ware 2002: Computing in an Imperfect World. Soft-Ware 2002. Lecture Notes in Computer Science, vol 2311. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46019-5_17

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  • DOI: https://doi.org/10.1007/3-540-46019-5_17

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43481-8

  • Online ISBN: 978-3-540-46019-0

  • eBook Packages: Springer Book Archive

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